Recent progress in digital signal processing and computer technology has been closely correlated with the increased demands for computer assisted radiographic processing in the health-care field. Technologic limitations unfortunately restrict the conversion of regular medical radiographs to high spatial resolution digital images. High resolution digital images can, however, be derived from dental or other radiographs several inches in size. Most of the existing high spatial resolution digitizers (e.g. the CCD video camera, the CCD scanner for the desk top publishing or the x-ray fluorescence plate with laser beam scanner) suffer from similar problems of unacceptable feature position accuracy, poor gray level reproduction, high costs and suitable for only particular applications. Such concerns limit their general health care applications.
Radiographs serve as invaluable adjuncts to dental treatment planning and progress assessments, in addition to providing records for subsequent referral. They are traditionally examined by dentists (or specialists) with minimal assistance, except for the occasional use of some form of magnifying device. Dental radiographic assessments are therefore largely subjective, primarily dependent on the clinician's prior experience. In the cases where contrasts are small (e.g. incipient carious lesions), the objects are small and irregular (e.g. apex of a tooth during root canal therapy) or the changes between sequential radiographs are incremental (e.g. alveolar bone changes following periodontal therapy). Quantitative diagnoses or evaluations are often difficult by simple visual inspection.
With recent advances in digital image processing and computer technology, clinicians have demanded computer aided radiographic processing to assist their diagnoses (e.g. cardiography, mammography). In a dental setting, the diagnostic and evaluative contributions of conventional radiographs can be extended by the application of precise image enhancement techniques. This is particularly important, since film-based radiographs are unlikely to be replaced as diagnostic or evaluative tools in the near to medium-term future, i.e. alternative imaging systems, e.g. ultrasound and other forms of imaging, are unlikely to rival the cost efficiency of dental radiographs.
The research literature contained in the 164 research papers published in 1992 illustrates the immense potential by employing the digital image technology to routine clinical dental practice. If capital costs can be reduced, such advances will be available to clinical practice, rather than being confined to the research laboratory.
Traditional radiographs must be converted to digital images prior to the application of computer-aided image processing techniques. But whereas such techniques can improve image sharpness and reduce extraneous noise (FIG. 1), the equipment is expensive and difficult to use. As a consequence, digital image processing techniques are largely confined to the research laboratory, and practicing dentists must continue to rely upon crude techniques for radiographic image magnification. The lack of clear radiographic images also restricts their value in patient communication.
The principal determinants impacting on the quality of a radiographic image include image noise, image sharpness and image distortion. The relationships between each of these determinants are, however, complex. For instance, the image blur is a function of receptor spatial resolution, whereas image contrast is a function of receptor amplitude response. Digital images also suffer from additional quality degradation during the conversion from the analog, continuous form to digital format.
Many forms of commercial equipment can be used to convert radiograph to digital images. Examples include commercial video cameras, image scanners for desk top publishing, image scanners for mammography, x-ray fluorescence storage plate with laser scanner, etc. Yet all these device have a number of inherent problems. For instance, the x-ray fluorescence storage plate is bulky, expensive and unsuitable for routine dental radiography. The image scanner has many advantages compared to video cameras, e.g. a better dynamic range in the image gray level and better spatial resolution. Yet it suffers unacceptable geometric distortion due to an inaccurate scanning process. Both the image scanner and video camera suffer from distortion in duplicating the radiographic optical density readings. This is caused mainly by the CCD dark current, the scattered diffusing light and the analog to digital converter (8-bit) 256 gray level constraint. The mammograph laser scanner has very good linear relationship between the film optical density and the digital image gray level, but suffers the inaccurate feature position reproduction. This deficiency is of no consequence for mammograms, where positioning has little diagnostic consequence.
The simplest digitization method involves the use of a CCD (Charge-Coupled-Device) camera (i.e. a commercial video camera, camcorder or equivalent) to project the radiograph onto the camera image plane. Unfortunately, commercial video cameras have many shortcomings, severely limiting the resultant digital image quality and consequent quantitative accuracy. Such limitations applied to radiographic digitization include the following:
(i). Low spatial resolution: PA0 (ii). Low dynamic range: PA0 (iii). Timing errors: PA0 (iv). Defective CCD elements:
The image plane of a commercial video camera comprises an area array of CCD elements of approximately 600.times.480. Each element has nominal size of 10 .mu.m.times.10 .mu.m (element size is in the 6 to 20 .mu.m range depending on the manufacturer and the model number, and elements may be occasionally rectangular instead of square). The resultant digitized image is therefore represented by 600.times.480 squares, with the amplitude of each square being the average of the original image at the corresponding area. If the original document is 40.times.30 mm, the spatial resolution for such digital image is approximately 67 .mu.m.
The first technique for improving the spatial resolution of a video-based system involves the use of a large CCD area array, say 2048.times.2048, but the equipment costs become a major concern. Whereas a commercial video camera can be purchased for approximately $1,000 and a 2048.times.2048 CCD camera costs approximately $20,000.
Alternatively, spatial resolution can be enhanced by reducing the area covered. With this technique, the original document will comprise a series of multiple digital images. A precision mechanical setup is then required to combine such multiple digital images to a single image.
Because of the video camera design specification, the CCD element amplitude response dynamic range is usually around 3,000:1 or lower and it gives poor contrast. The resultant digital image gray level has no variations at densities greater than 1 ODU (optical density units). Secondly, the scattered diffusing light from radiograph illumination increases the CCD camera background noise, subsequently reducing the dynamic range. Thirdly, the dark current accumulated in the CCD element due to the time delay between the exposure and the reading is very high which degrades the dynamic range. (For example, if the CCD array has a maximum frame rate of 100 frames per sec, typical frame speed is much less, the time delay between the exposure and the reading of last CCD element is 10 msec. This is a very long delay.)
In order to read the CCD elements efficiently and rapidly, each must be read line by line. Timing jitters in reading the CCD array and/or converting the analog to the digital signal will lead to the digital image distortion. A displacement of a few pixels between each line is not uncommon, whereas keeping the timing error to less than one pixel is not a simple inexpensive task.
Manufacturers are currently capable of supplying zero defective elements for an area array size of 512.times.512, whereas the industrial standard of a scientific grade area array of 1024.times.1024 elements has 10 defective elements, A zero defective element in a 2048.times.2048 array would be extremely difficult to delineate with current technology and very expensive. For instance, a scientific grade CCD area array of 2048.times.2048 may have less than 150 defective pixels compared to 600 defective pixels for the commercial grade. Such scientific grade systems cost two to three times more (i.e. $40-60,000).
Based on the above, therefore, an accurate and economically viable radiograph digitizer is not feasible at this time, despite the obvious clinical demands. The majority of published research reports dealing with various forms of digital image processing technology are confined to the research laboratory: the advantages of such technology is not yet available to the dentist, due to the high associated costs.